Covid Report for Family

Background

Notes and format last updated Apr 16, 2020

• This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
• The table of contents above summarizes the major sections and can be used to jump to those sections.
• Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
  • If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
• More detailed descriptions and context can be found in each section.

Growth rates

Heat maps

• The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
• The first plot compares growth rate for total cases; the second, growth rate for total deaths.
• The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
• The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
  • You can use the plots to track each geography over time and to compare the geographies to one another.
  • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

• This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of large day-to-day discrepancies in new case reporting at the state level.
  • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero because total cases can never go down. We at least want them to get as close to zero as possible.
  • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis and that we’re on the other side of the “apex.”

U.S.

Our states

Death growth rates

• This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
  • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
• Each of these two lines using rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of large day-to-day discrepancies in new death reporting at the state level.
  • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero because total deaths can never go down. We at least want them to get as close to zero as possible.
  • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis and that we’re on the other side of the “apex.”

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

• This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
• For each metric, in addition to the tables, the trends for the top states are plotted over time.
  • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)

State	Cases Per Million
New York	14,505
New Jersey	11,880
Massachusetts	7,740
Connecticut	6,894
Rhode Island	6,729
Louisiana	5,702
District of Columbia	5,241
Michigan	3,723
Delaware	3,672
Illinois	3,296
Pennsylvania	3,251
Maryland	2,938
South Dakota	2,426
Colorado	2,251
Indiana	2,138
Georgia	2,093
Mississippi	1,921
Washington	1,770
Iowa	1,619
Nebraska	1,500
Nevada	1,473
Virginia	1,448
Florida	1,435
Vermont	1,350
Ohio	1,333
New Hampshire	1,318
Tennessee	1,314
New Mexico	1,269
Alabama	1,267
Utah	1,232
Missouri	1,112
California	1,071
Kansas	1,057
North Dakota	1,053
South Carolina	1,020
Idaho	984
Wisconsin	976
Arkansas	963
Kentucky	874
Arizona	862
Texas	844
North Carolina	822
Oklahoma	806
Maine	736
Wyoming	625
Minnesota	611
West Virginia	571
Oregon	534
Alaska	460
Hawaii	421
Montana	416
Puerto Rico	409
Guam	NA
Northern Mariana Islands	NA
Virgin Islands	NA

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)

State	New Cases Per Million
Massachusetts	503
New York	427
Rhode Island	405
New Jersey	362
District of Columbia	232
Connecticut	197
Nebraska	185
Illinois	175
Maryland	164
Iowa	142
Delaware	128
Pennsylvania	126
Colorado	120
Michigan	108
South Dakota	108
Indiana	96
Mississippi	92
Kansas	90
Louisiana	89
Virginia	82
New Mexico	71
Georgia	66
Tennessee	62
Arkansas	57
North Dakota	54
Utah	51
New Hampshire	50
Nevada	49
Wisconsin	48
North Carolina	44
Minnesota	42
Ohio	41
Washington	41
Alabama	40
California	40
Puerto Rico	40
Florida	39
Kentucky	39
Arizona	37
Missouri	37
South Carolina	31
Texas	31
Oklahoma	25
Maine	20
Wyoming	20
Oregon	15
West Virginia	15
Idaho	13
Vermont	10
Hawaii	2
Alaska	1
Montana	1
Guam	NA
Northern Mariana Islands	NA
Virgin Islands	NA

Total deaths

Table of total deaths per million residents (all 50 states)

State	Deaths Per Million
New York	853
New Jersey	660
Connecticut	522
Massachusetts	396
Louisiana	353
Michigan	327
District of Columbia	233
Rhode Island	202
Illinois	148
Pennsylvania	143
Maryland	131
Colorado	116
Indiana	116
Delaware	115
Washington	97
Georgia	84
Mississippi	74
Vermont	73
Nevada	66
Ohio	60
Virginia	51
Florida	49
Oklahoma	49
Kentucky	46
Missouri	45
Wisconsin	45
New Hampshire	44
New Mexico	44
Alabama	43
Minnesota	43
California	42
Kansas	40
Arizona	37
Maine	37
Iowa	35
South Carolina	32
Idaho	31
North Carolina	28
Nebraska	27
Tennessee	27
Texas	22
North Dakota	20
Oregon	20
West Virginia	18
Puerto Rico	16
Arkansas	15
Montana	13
Utah	12
Wyoming	12
South Dakota	11
Alaska	9
Hawaii	9
Guam	NA
Northern Mariana Islands	NA
Virgin Islands	NA

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)

State	New Deaths Per Million
New Jersey	30
Connecticut	29
Massachusetts	26
New York	22
District of Columbia	17
Michigan	15
Louisiana	12
Rhode Island	10
Maryland	9
Colorado	8
Illinois	8
Delaware	7
Indiana	6
Minnesota	3
Mississippi	3
New Mexico	3
Pennsylvania	3
Vermont	3
Virginia	3
California	2
Iowa	2
Maine	2
Missouri	2
Nevada	2
New Hampshire	2
Ohio	2
Oklahoma	2
Washington	2
Arizona	1
Florida	1
Georgia	1
Kentucky	1
Nebraska	1
North Carolina	1
South Carolina	1
Texas	1
Wisconsin	1
Alabama	0
Alaska	0
Arkansas	0
Hawaii	0
Idaho	0
Kansas	0
Montana	0
North Dakota	0
Oregon	0
Puerto Rico	0
South Dakota	0
Tennessee	0
Utah	0
West Virginia	0
Wyoming	0
Guam	NA
Northern Mariana Islands	NA
Virgin Islands	NA

Counties

• This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
  • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
• In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Cases Per Million	Raw Ranking	Percentile
New York	New York	95,244	1	99
Lincoln	Arkansas	55,359	2	99
Bledsoe	Tennessee	38,901	3	99
Rockland	New York	34,044	4	99
Marion	Ohio	33,368	5	99
Davidson	Tennessee	3,188	215	93
Richland	South Carolina	1,893	442	85
Pierce	Washington	1,451	589	81
York	South Carolina	630	1272	59
Orange	California	620	1286	59

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.

County	State	Deaths Per Million	Raw Ranking	Percentile
New York	New York	7,011	1	99
Randolph	Georgia	2,803	2	99
Terrell	Georgia	1,993	3	99
Early	Georgia	1,472	4	99
Nassau	New York	1,413	5	99
Pierce	Washington	52	655	79
Richland	South Carolina	43	741	76
Davidson	Tennessee	32	901	71
Orange	California	12	1228	60
York	South Carolina	11	1247	60

Our county percentiles over time

Raw counts

• This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
  • Total confirmed cases: This is the cumulative total of cases reported.
  • New confirmed cases: This is the number of new cases reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new cases, to help better visualize the peak.
  • Total deaths: This is the cumulative total of deaths reported.
  • New deaths: This is the number of new deaths reported on each respective date.
    • For the U.S. and states, a trendline shows the rolling 7-day average of new deaths, to help better visualize the peak.

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons

• This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
  • The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
    • So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
    • Over time (if the policies work), what we’d expect is that the line for the group with orders flattens or declines in relation to the no-order group. It also may become moot if all states issue orders.
    • As states start rescending their orders, I’ll put them back into the no-order group, so the no-order group should beging to expand again.
  • The second plot tracks progress of states by the number of days since orders have been in effect. It includes only those states with orders and shows their average new case growth rate (a rolling 3-day average of daily growth rates) based on how long it’s been since the order went into effect. Again, the size of the dots show how many states are included in each point – i.e., as you go further right, the dots are smaller because less states are that far past their order.
    • I’m working on how to add a baseline to this chart to compare to states without orders, but that’s challenging because there’s no way to fully align timing.